The disclosure is related to a system and a method for collision avoidance for vehicle. In the method, the system predicts multiple routes of an abnormal vehicle in a period of time according to historical data when a nearby vehicle receives an alert from the abnormal vehicle. A route potential pattern can be created when the system gets the historical data. The system also computes one or more available routes for the nearby vehicle based on its vehicle information. Every available route has its collision risk value. The system finally provides a recommended route with lower collision risk value when it considers a time of the abnormal vehicle reaches its great change, a time of predicting the nearby vehicle meets the range of route potential pattern, and a safe distance there-between.
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1. A method for collision avoidance for vehicle, comprising: an avoidance system installed in a first vehicle receiving an abnormal signal from an abnormal vehicle; the avoidance system predicting at least one predicted traveling route for the abnormal vehicle within a period of time according to historical data with respect to the abnormal signal and vehicle information of the abnormal vehicle; the avoidance system providing at least one recommended route for the first vehicle within the period of time based on the at least one predicted traveling route; the avoidance system computing a collision risk value for every recommended route for the first vehicle; and the avoidance system deciding a best recommended route for the first vehicle to avoid the abnormal vehicle according to the collision risk value corresponding to every recommended route.
A collision avoidance system for vehicles uses an avoidance system installed in a first vehicle. When the first vehicle receives an alert signal from another vehicle (designated as abnormal), the system predicts one or more potential routes that the abnormal vehicle might take within a specific timeframe. This prediction uses historical data associated with that type of alert signal and the abnormal vehicle's data. Based on these predicted routes, the system calculates one or more recommended routes for the first vehicle. For each recommended route, the system computes a collision risk value. Finally, it selects the best recommended route for the first vehicle by choosing the route with the lowest collision risk, thus avoiding a potential collision with the abnormal vehicle.
2. The method as recited in claim 1 , wherein the step of recommending the at least one recommended route for the first vehicle further comprises: the avoidance system acquiring vehicle information of the first vehicle, the vehicle information including at least one of operating statuses of gas pedal, brake, and steering wheel; and the avoidance system deciding the recommended route according to the predicted traveling route for the abnormal vehicle and the vehicle information of the first vehicle.
Building upon the collision avoidance system where the system installed in a first vehicle receives an abnormal signal from an abnormal vehicle, predicts routes for the abnormal vehicle using historical data, provides recommended routes for the first vehicle, computes collision risk values, and selects the best route based on risk, the step of recommending routes for the first vehicle also involves acquiring vehicle information from the first vehicle. This information includes operating statuses related to the gas pedal, brake, and steering wheel. The system then uses both the predicted routes of the abnormal vehicle and the real-time operational data of the first vehicle to determine the most suitable recommended route for the first vehicle.
3. The method as recited in claim 1 , wherein, the avoidance system configures the route with the lowest collision risk value as the best recommended route.
Extending the collision avoidance system where the system installed in a first vehicle receives an abnormal signal from an abnormal vehicle, predicts routes for the abnormal vehicle using historical data, provides recommended routes for the first vehicle, computes collision risk values, the route with the lowest collision risk value is automatically designated as the best recommended route for the first vehicle to take, further optimizing avoidance of the abnormal vehicle.
4. The method as recited in claim 1 , wherein the historical data is recorded in a database, the method to establish the database comprises: the avoidance system receiving driving event information corresponding to the abnormal signal generated by the abnormal vehicle when the avoidance system receives the abnormal signal; and the avoidance system categorizing the driving event information based on similarity, wherein the driving event information includes at least one of an abnormal code, a collision, an event time, a vehicle location, a vehicle speed, a vehicle acceleration, a vehicle direction, and climate corresponding to the abnormal signal.
In the collision avoidance system, historical data about abnormal vehicle events is stored in a database. To populate this database, when the system receives an alert signal generated by an abnormal vehicle, it also receives driving event information related to that signal. This information includes elements like an abnormal code associated with the signal, whether a collision occurred, the time of the event, the vehicle's location, speed, acceleration, direction, and even the prevailing climate conditions at the time. The system then categorizes this driving event information based on similarity, grouping together events with similar characteristics, to improve prediction accuracy in the future.
5. The method as recited in claim 4 , wherein the step of computing the collision risk value for every recommended route for the first vehicle is performed based on whether or not the recommended route for the first vehicle enters a route potential pattern of the abnormal vehicle; wherein the method for creating the route potential pattern comprises: the avoidance system drawing the at least one predicted traveling route for the abnormal vehicle on a grid map; and accumulating number of times of the at least one predicted traveling route passing through each grid of the grid map, and the route potential pattern is produced based on a proportion calculation.
Within the collision avoidance system, after the historical data database is established by receiving driving event information corresponding to the abnormal signal and categorizing the driving event information based on similarity including an abnormal code, a collision, an event time, a vehicle location, a vehicle speed, a vehicle acceleration, a vehicle direction, and climate, the process of computing the collision risk for each recommended route for the first vehicle is performed by checking if the route for the first vehicle crosses into a "route potential pattern" of the abnormal vehicle. Creating this pattern involves drawing the predicted routes of the abnormal vehicle on a grid map. The system counts how many times each predicted route passes through each grid square. The route potential pattern is then generated based on the frequency with which routes traverse specific grid squares, highlighting areas where the abnormal vehicle is more likely to travel.
6. The method as recited in claim 5 , further comprising: providing the best recommended route for the first vehicle if the avoidance system determines that a distance between the first vehicle and the abnormal vehicle is smaller than a safety distance; and if the avoidance system determines the distance between the first vehicle and the abnormal vehicle is larger than the safety distance, the avoidance system repeatedly computing the collision risk value for one or more recommended routes for the first vehicle in every time interval until the collision risk value is found to be lower than then a risk threshold, and instantly the corresponding route configured to be the best recommended route for the first vehicle.
Continuing from the collision avoidance system that creates a route potential pattern for the abnormal vehicle, the system further provides the best recommended route for the first vehicle immediately if the distance between the first vehicle and the abnormal vehicle is less than a defined safety distance. However, if the distance is greater than the safety distance, the system continuously recalculates the collision risk value for the available recommended routes at regular time intervals. This process repeats until a route is found with a collision risk value lower than a predefined risk threshold. The route with the collision risk below the risk threshold is then selected as the best recommended route for the first vehicle.
7. The method as recited in claim 5 , further comprising: providing the best recommended route for the first vehicle if the avoidance system determines that a distance between the first vehicle and the abnormal vehicle is smaller than a safety distance; and if the avoidance system determines the distance between the first vehicle and the abnormal vehicle is larger than the safety distance, the avoidance system repeatedly computing the collision risk value for one or more recommended routes for the first vehicle in every time interval and an instant best recommended route until the abnormal vehicle reaches a great change; the instant best recommended route configured to be the best recommended route for the first vehicle.
Expanding on the collision avoidance system that creates a route potential pattern for the abnormal vehicle, the system provides an immediate best recommended route if the distance between the first vehicle and the abnormal vehicle is less than a defined safety distance. If the distance is greater, the system continuously recalculates the collision risk value for the available recommended routes at regular time intervals and determines an instant best recommended route. This iterative process continues until the abnormal vehicle experiences a significant change in its behavior (e.g., a drastic change in speed or direction). The instant best recommended route that was determined at the time of this change is then set as the final best recommended route for the first vehicle.
8. The method as recited in claim 5 , further comprising: the avoidance system acquiring driving event information for the database based on similarity in response to the abnormal signal generated by the abnormal vehicle, acquiring a great change time from normal to abnormal of the abnormal vehicle, and computing a great change distance from normal to abnormal of the abnormal vehicle according to the great change time; the avoidance system acquiring a traveling route of the first vehicle according to vehicle information of the first vehicle, and computing a potential distance when the first vehicle is estimated to enter the route potential pattern of the abnormal vehicle; the avoidance system comparing the great change distance or the potential distance, whichever is smaller, with a safety distance; the avoidance system providing the best recommended route for the first vehicle if the avoidance system determines the great change distance or the potential distance, whichever is smaller, is smaller than the safety distance; and if the avoidance system determines the great change distance or the potential distance, whichever is smaller, is larger than the safety distance, the avoidance system periodically computing the collision risk value for every recommended route for the first vehicle to avoid the abnormal vehicle in every time interval until the collision risk value is found to be lower than a risk threshold, and the corresponding route with instant lowest collision risk value configured to be the best recommended route.
Building upon the collision avoidance system that uses a database of categorized driving events, this version also considers the point at which the abnormal vehicle's behavior changes from normal to abnormal. The system acquires this "great change time" and calculates a "great change distance" based on it. It also assesses the first vehicle's trajectory, computing a "potential distance" indicating when the first vehicle might enter the abnormal vehicle's route potential pattern. The system compares the smaller of either the "great change distance" or the "potential distance" against a defined safety distance. If this smaller distance is less than the safety distance, a best recommended route is immediately provided. Otherwise, the system periodically computes collision risk values for each recommended route until a route is found with a risk value below a threshold, making that route the best recommendation.
9. The method as recited in claim 4 , wherein the avoidance system does not record the vehicle information corresponding to the abnormal signal when the avoidance system detects that the abnormal vehicle slows down after receiving the abnormal system generated by the abnormal vehicle.
In the collision avoidance system that uses a database to store and categorize driving event information corresponding to abnormal signals, when the avoidance system detects that the abnormal vehicle is slowing down after generating the abnormal signal, the system will *not* record the vehicle information corresponding to the abnormal signal. This prevents the database from being populated with potentially misleading data from situations where the abnormal event is quickly resolved.
10. The method as recited in claim 4 , wherein, after receiving the abnormal signal generated by the abnormal vehicle, the avoidance system further receives vehicle information from a second vehicle so as to acquire the second vehicle's traveling route within the period of time; and the avoidance system re-computes the collision risk value according to traveling routes of the first vehicle, the second vehicle and the abnormal vehicle for re-arranging the recommended route to avoid the abnormal vehicle.
Adding to the collision avoidance system that uses a database to store categorized driving events from abnormal signals, the system, after receiving an abnormal signal from an abnormal vehicle, also receives vehicle information from a second vehicle, acquiring the second vehicle's predicted route. The system then re-computes the collision risk values, considering the routes of the first vehicle, the second vehicle, and the abnormal vehicle. Based on these updated risk values, it re-arranges the recommended route for the first vehicle to optimally avoid the abnormal vehicle, now taking into account the presence and movement of other nearby vehicles.
11. A system for collision avoidance for vehicle, installed in a nearby vehicle near an abnormal vehicle, comprising: a signal receiving unit, used to receive signals from a nearby vehicle, and signals from the abnormal vehicle; a vehicle information acquiring unit, retrieving vehicle information from the signals obtained from the signal receiving unit; an abnormal signal acquiring unit, retrieving the abnormal signal from every vehicle's vehicle information and obtaining historical data as comparing the abnormal signal with a database, for analyzing a predicted traveling rout of the abnormal vehicle; a potential figure creating unit, forming a route potential pattern having multiple potential routes according to the historical data corresponding to the abnormal vehicle from the abnormal signal acquiring unit; a route risk estimating unit, acquiring one or more recommended routes according to vehicle information of the nearby vehicle, and computing collision risk value for every recommended route; a route determination unit, acquiring distance relationship between the vehicles, and providing the recommended route with the lowest collision risk value based on whether or not a distance between the nearby vehicle and the abnormal vehicle is smaller than a safety distance; and an output unit, used to output the recommended route generated from the route determination unit to the nearby vehicle.
A collision avoidance system designed for a vehicle near an abnormal vehicle includes several key components. A signal receiving unit gathers signals from nearby vehicles, including the abnormal one. A vehicle information acquiring unit extracts data from these signals. An abnormal signal acquiring unit identifies the abnormal signal, compares it to historical data in a database, and predicts the abnormal vehicle's route. A potential figure creating unit constructs a route potential pattern from historical data. A route risk estimating unit determines routes for the nearby vehicle and computes collision risk for each. A route determination unit considers distances between vehicles and selects the lowest-risk route based on a safety distance threshold. Finally, an output unit displays the recommended route to the nearby vehicle's driver.
12. The system as recited in claim 11 , wherein the avoidance system is installed in at least one vehicle, and a wireless communication network is provided among the vehicles for transmitting signals.
Building on the collision avoidance system that includes a signal receiving unit, a vehicle information acquiring unit, an abnormal signal acquiring unit, a potential figure creating unit, a route risk estimating unit, a route determination unit, and an output unit, the avoidance system is installed in multiple vehicles. These vehicles are interconnected through a wireless communication network, which facilitates the exchange of signals and data among them, allowing for a more coordinated and comprehensive collision avoidance strategy across multiple vehicles.
13. The system as recited in claim 11 , wherein the route determination unit estimates distance relationship between the vehicles according to a time that the abnormal vehicle becomes from normal to abnormal status, a time that the nearby vehicle enters the route potential pattern of the abnormal vehicle, and a safe time between the abnormal vehicle and the nearby vehicle.
Further specifying the collision avoidance system that has a signal receiving unit, a vehicle information acquiring unit, an abnormal signal acquiring unit, a potential figure creating unit, a route risk estimating unit, a route determination unit, and an output unit, the route determination unit estimates distances between vehicles using three key factors: the time the abnormal vehicle transitioned from normal to abnormal status, the time the nearby vehicle is predicted to enter the abnormal vehicle's route potential pattern, and a pre-defined safe time interval to maintain separation between the vehicles. This temporal analysis helps in proactive risk assessment and route planning.
14. The system as recited in claim 13 , wherein the route determination unit introduces a risk threshold to determine if the best recommended route with the lower collision risk value is obtained.
Expanding the collision avoidance system that has a signal receiving unit, a vehicle information acquiring unit, an abnormal signal acquiring unit, a potential figure creating unit, a route risk estimating unit, a route determination unit estimating distance relationship between the vehicles according to a time that the abnormal vehicle becomes from normal to abnormal status, a time that the nearby vehicle enters the route potential pattern of the abnormal vehicle, and a safe time between the abnormal vehicle and the nearby vehicle, and an output unit, the route determination unit uses a pre-defined risk threshold. This threshold is used to confirm that the selected best recommended route truly offers an acceptably low collision risk value, ensuring a safe and reliable route selection process.
15. The system as recited in claim 11 , wherein the information acquired by the vehicle information acquiring unit includes at least one piece of operating data of gas pedal, brake and steering wheel.
Within the collision avoidance system that includes a signal receiving unit, an abnormal signal acquiring unit, a potential figure creating unit, a route risk estimating unit, a route determination unit, and an output unit, the vehicle information acquiring unit gathers data pertaining to the gas pedal, brake, and steering wheel. This provides crucial information about the vehicle's current operational state.
16. The system as recited in claim 11 , wherein the abnormal signal acquired by the abnormal signal acquiring unit includes trouble code and its corresponding vehicle information.
Regarding the collision avoidance system that uses a signal receiving unit, a vehicle information acquiring unit, a potential figure creating unit, a route risk estimating unit, a route determination unit, and an output unit, the abnormal signal acquiring unit retrieves trouble codes (diagnostic codes indicating a malfunction) along with associated vehicle information.
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December 3, 2015
July 11, 2017
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